Blog · Coverage and territory · Consumer goods
Retail execution analytics connects store audits, authorized assortments, promotion requirements and sales. Build a scorecard with explicit coverage and availability denominators, reconcile the records, and assign follow-up work.
Retail execution analytics compares what was supposed to happen in a store with what an audit found and what the store sold. For a consumer packaged goods team, that means the authorized item was available, the promotion met its requirements, and the sales records cover the same store and product. The result should be a follow-up list with evidence and an owner.
A store can be authorized to carry an item without having it on the shelf. It can have stock without displaying the promotional price. It can also sell well despite an isolated failed check. Keep these conditions visible instead of combining them into a single unexplained performance score.
The retail analytics overview covers broader merchandise performance. Execution analysis focuses on whether an agreed store activity occurred and what evidence supports that conclusion.
Start with a question an account manager can act on: which authorized items had observed availability failures, which eligible promotions missed requirements, and which records still need a completed visit? A sales manager owns the commercial follow-up, a field manager validates the observation, and the retailer relationship owner agrees the corrective action.
Use an authorized assortment list containing retailer, store identifier, product identifier and effective dates. Add the audit export with observation date, item, shelf status and completed-check status. Add the promotion agreement with eligible stores, products, dates and required conditions. Finally, bring sales units and net merchandise revenue for the same period.
Store names and product descriptions are weak matching fields. Where trading partners use them, GS1 US explains that a Global Location Number identifies parties and locations while a Global Trade Item Number identifies products. Otherwise, use a reviewed cross-reference between each export's stable identifiers.
Choose one audit record per store, product and scheduled check. Resolve repeated visits explicitly: retain the agreed scheduled observation or report repeat checks separately. Aggregate sales to store-product-period before combining them with the scorecard. Otherwise, several visits can repeat one sales total and inflate revenue.
For the sales view, use merchandise revenue after refunds and allowances and exclude sales tax. Those treatments align with the Census Bureau's retail sales definitions. Keep manufacturer shipments separate from retailer sell-through; they describe different transactions.
An illustrative US packaged-food brand reviews Cedar and Maple stores for October 12–18, 2026. Both stores are authorized for Tea and Snack throughout the period. Each store-product pair has four scheduled shelf checks. Tea is promoted at both stores; Snack is promoted only at Maple.
An observation is completed only when the auditor records shelf status. A compliant promotion observation meets every condition in the relevant agreement. The following counts have already been checked for duplicate observations.
| Store | SKU | Planned checks | Completed checks | Shelf-present checks | Completed promotion-eligible checks | Compliant promotion checks |
|---|---|---|---|---|---|---|
| Cedar | Tea | 4 | 4 | 3 | 4 | 3 |
| Cedar | Snack | 4 | 4 | 4 | 0 | 0 |
| Maple | Tea | 4 | 3 | 1 | 3 | 1 |
| Maple | Snack | 4 | 1 | 0 | 1 | 0 |
| Total | 16 | 12 | 8 | 8 | 4 |
Audit coverage = Completed checks / Planned eligible checks
Observed shelf availability = Shelf-present checks / Completed eligible shelf checks
Observed promotion compliance = Compliant checks / Completed promotion-eligible checks
Coverage is 12 / 16 = 75.0%. Observed availability is 8 / 12 = 66.7%, and promotion compliance is 4 / 8 = 50.0%. Percentages are rounded to one decimal place after calculating from the counts.
There are 16 − 12 = 4 missing checks, 12 − 8 = 4 observed shelf failures, and 8 − 4 = 4 observed promotion failures. Cedar Snack contributes completed shelf observations but no promotion observations because it is outside the promotion. Giving it a promotion failure would penalize work nobody agreed to perform.
These are the complete sales totals for the same authorized store-product pairs and week. Actual net unit prices are constant within each row in this illustration.
| Store | SKU | Net units sold | Net price per unit (USD) | Net revenue (USD) |
|---|---|---|---|---|
| Cedar | Tea | 36 | 4 | 144 |
| Cedar | Snack | 20 | 5 | 100 |
| Maple | Tea | 12 | 4 | 48 |
| Maple | Snack | 8 | 5 | 40 |
| Total | 76 | 332 |
The revenue check is 36 × 4 + 20 × 5 + 12 × 4 + 8 × 5 = $332. Cedar contributes 36 + 20 = 56 units and 144 + 100 = $244; Maple contributes 12 + 8 = 20 units and 48 + 40 = $88. Store totals must match the original sales export before interpreting the execution comparison.
Maple has both lower sales and more availability issues in the observed checks. That supports an investigation, but it does not prove the failures caused the entire sales difference. The stores may have different customer demand, selling space or operating hours. A shelf check is a point-in-time observation, not a record of availability throughout the week.
Use pricing analytics in retail when the question shifts to the effect of price. Keep that analysis separate from whether a promotion's agreed price and display were present.
Maple Snack has no shelf-present result in its one completed observation, with the remaining scheduled observations missing. The first follow-up is to verify current availability and complete the missing evidence. It would be misleading to describe the item as unavailable throughout the review period.
Maple Tea has repeated observed shelf failures and incomplete promotion compliance. Ask the account owner to validate replenishment and the field owner to check the promotion conditions. Store the underlying audit reference, requirement, due date and next verification alongside that action in the team's existing tracker.
For each review, show authorized pairs without any observation, observed failures, and resolved issues awaiting a repeat check. Keep the denominator counts beside the rates so improving coverage cannot be mistaken for deteriorating execution. Retail operations analytics handles the separate question of store labor, costs and operating efficiency.
Bring a sample of your own store-SKU audit summaries, promotion requirements and sales exports to Covirage; it maps the columns, and its tools compute and check coverage, availability, compliance and sales totals. The external AI model explains the comparison with every figure traced to its rows. Create a free Covirage account, then set up your business and bring your file.
See Covirage for CPG brands for the supporting industry context.
For a defined set of checks, divide observations where the item was present on the shelf by completed eligible shelf observations. Report audit coverage separately. A missing audit is unknown, while an observed empty shelf is a failure; combining them hides the evidence quality.
Promotion compliance is the share of completed eligible checks that meet the stated promotion requirements. Define whether compliance requires price, display and timing together or measures each separately. Products and stores outside the agreed promotion should not enter the denominator.
Audit and sales exports can identify availability failures alongside weaker sales, but that comparison alone does not establish lost sales. Demand, store size, price and other factors may differ. Label any lost-sales estimate as an assumption-based scenario and show its comparison method.